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Qiwei Ge et al. Artif Intell Med 2024 153102887
The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis.
Yuefei Li et al. BMC Infect Dis 2024 24(1) 474
The role of community engagement in promoting research participants' understanding of pharmacogenomic research results: Perspectives of stakeholders involved in HIV/AIDS research and treatment.
Sylvia Nabukenya et al. PLoS One 2024 19(4) e0299081
Concerted efforts toward genomic surveillance of viral pathogens in immunocompromised individuals.
Matheus Filgueira Bezerra et al. Lancet Microbe 2024 4
Machine learning prediction of adolescent HIV testing services in Ethiopia.
Melsew Setegn Alie et al. Front Public Health 2024 121341279
A Machine Learning Approach to Predict HIV Viral Load Hotspots in Kenya Using Real-World Data.
Nancy Kagendi et al. Health Data Sci 2024 30019
Development of a Machine Learning Modelling Tool for Predicting HIV Incidence Using Public Health Data from a County in the Southern United States.
Carlos S Saldana et al. Clin Infect Dis 2024
A Bayesian approach for investigating the pharmacogenetics of combination antiretroviral therapy in people with HIV.
Wei Jin et al. Biostatistics 2024
Supervised machine learning algorithms to predict the duration and risk of long-term hospitalization in HIV-infected individuals: a retrospective study.
Jialu Li et al. Front Public Health 2024 111282324
Use of a machine learning model to predict retention in care in an urban HIV clinic.
Sarah A Schmalzle et al. AIDS 2023 38(1) 125-127
Patient-Level Exposure to Actionable Pharmacogenomic Medications in a Nationally Representative Insurance Claims Database.
Monica L Bianchini et al. J Pers Med 2023 13(11)
A Machine Learning Approach to Predict Weight Change in ART-Experienced People Living With HIV.
Federico Motta et al. J Acquir Immune Defic Syndr 2023 94(5) 474-481
Comparison of logistic regression with regularized machine learning methods for the prediction of tuberculosis disease in people living with HIV: cross-sectional hospital- based study in Kisumu County, Kenya.
James Orwa et al. Res Sq 2023
Deep Learning Classification of Tuberculosis Chest X-rays.
Kartik K Goswami et al. Cureus 2023 15(7) e41583
Validation of Automated Visual Evaluation (AVE) on Smartphone Images for Cervical Cancer Screening in a Prospective Study in Zambia.
Liming Hu et al. medRxiv 2023
Historical visit attendance as predictor of treatment interruption in South African HIV patients: Extension of a validated machine learning model.
Rachel T Esra et al. PLOS Glob Public Health 2023 3(7) e0002105
Suddenly, It Looks Like We’re in a Golden Age for Medicine We may be on the cusp of an era of astonishing innovation — the limits of which aren’t even clear yet.
DW Wells, New York Times. June 23, 2023
WHO Introduces Worldwide Pathogen Surveillance Network
E Harris, JAMA, June 20, 2023
Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, Ethiopia, 2022.
Daniel Niguse Mamo et al. BMC Med Inform Decis Mak 23(1) 75
Predicting the HIV/AIDS Knowledge among the Adolescent and Young Adult Population in Peru: Application of Quasi-Binomial Logistic Regression and Machine Learning Algorithms.
Alejandro Aybar-Flores et al. Int J Environ Res Public Health 2023 20(7)
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Disclaimer: Articles listed in the Public Health Knowledge Base are selected by Public Health Genomics Branch to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.